A Unifying Framework for Invariant Pattern Recognition
A Unifying Framework for Invariant Pattern Recognition
We introduce a group-theoretic model of invariant pattern recognition, the Group Representation Network. We show that many standard invariance techniques can be viewed as GRNs, including the DFT power spectrum, higher order neural network and fast translation-invariant transform.
Invariant pattern recognition, Group theory, Discrete Fourier transform, Fast translation-invariant transform, Invariant neural networks, Higher-order networks
1415-1422
Wood, J.
65587872-7126-469a-851a-d60195d39058
Shawe-Taylor, J.
c32d0ee4-b422-491f-8c28-78663851d6db
December 1996
Wood, J.
65587872-7126-469a-851a-d60195d39058
Shawe-Taylor, J.
c32d0ee4-b422-491f-8c28-78663851d6db
Wood, J. and Shawe-Taylor, J.
(1996)
A Unifying Framework for Invariant Pattern Recognition.
Pattern Recognition Letters, 17 (0167-8), .
Abstract
We introduce a group-theoretic model of invariant pattern recognition, the Group Representation Network. We show that many standard invariance techniques can be viewed as GRNs, including the DFT power spectrum, higher order neural network and fast translation-invariant transform.
This record has no associated files available for download.
More information
Published date: December 1996
Keywords:
Invariant pattern recognition, Group theory, Discrete Fourier transform, Fast translation-invariant transform, Invariant neural networks, Higher-order networks
Organisations:
Electronics & Computer Science
Identifiers
Local EPrints ID: 250475
URI: http://eprints.soton.ac.uk/id/eprint/250475
PURE UUID: f1fea9ed-1aa1-45dc-8e62-7aaa42a5a3e3
Catalogue record
Date deposited: 16 Mar 2004
Last modified: 08 Jan 2022 14:40
Export record
Contributors
Author:
J. Wood
Author:
J. Shawe-Taylor
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics